\chapter{Introduction} 

Query represents the information need of user, by which retrieval systems are expected to fetch
relevant documents from the collection. Traditional information retrieval focuses on the frequency of word appearance, co-occurrence statistics to uncover the relationships among query and documents.

\section{Applications}


The aim of this work is to explore various methods related to improving information retrieval
utilizing the Semantic Web, ranking the relationships among concepts in the structured data
and combining the Semantic Web with full text search.

\section{Challenges}

\section{Roadmap}

The remaining part of this report organized as follows: Section 2 introduces the semantic web. Section 3 explains similarity measurements between concepts from ontology and using the similarity measures in the ranking system. Section 4 describes essence of integrated semantic full text search and Broccoli system. Section 5 is about ranking methods for ranking relationships between two concepts.
